Dynamic simulation of squeezing flow of ER fluids using parallel processing

Do Hoon Kim; Sang-Hyon Chu; Kyung Hyun Ahn; Seung Jong Lee

Korea-Australia Rheology Journal, Vol.11, No.3, 233-240, September, 1999

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Dynamic simulation of squeezing flow of ER fluids using parallel processing

Do Hoon Kim, Sang-Hyon Chu, Kyung Hyun Ahn¹, and Seung Jong Lee^†

School of Chemical Engineering and Institute of Chemical Processes, Seoul National University, Seoul 151-742, Korea
¹R&D Center, Cheil Industries Inc., Euiwang-shi Kyunggi-do 437-010, Korea

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In order to understand the flow behavior of Electrorheological (ER) fluid, dynamic simulation has been intensively performed for the last decade. When the shear flow is applied, it is easy to carry out the simulation with relatively small number of particles because of the periodic boundary condition. For the squeezing flow, however, it is not easy to apply the periodic boundary condition, and the number of particles needs to be increased to simulate the ER system more realistically. For this reason, the simulation of ER fluid under squeezing flow has been mostly performed with some representative chains or with the approximation that severely restricts the flow geometry to reduce the computational load. In this study, Message Passing Interface (MPI), which is one of the most widely-used parallel processing techniques, has been employed in a dynamic simulation of ER fluid under squeezing flow. As the number of particles used in the simulation could be increased significantly, full domain between the electrodes has been covered. The numerical treatment or the approximation used to reduce the computational load has been evaluated for its validity, and was found to be quite effective. As the number of particles is increased, the fluctuation of the normal stress becomes diminished and the prediction in general was found to be qualitatively in good agreement with the experimental results.

Keywords:Electrorheological fluid;Squeezing flow;Parallel processing;Normal stress;Yield stress

[References]

Adriani PM, Gast AP, Phys. Fluids, 31, 2757 (1988)
Ahn KH, Klingenberg DJ, J. Rheol., 38(3), 713 (1994)
Brady JF, Bossis G, Ann. Rev. Fluid. Mech., 20, 111 (1988)
Brooks DA, "Selection of Commercial ElectroRheological Device," in Proceedings of the Fourth International Conference on Electrorheological Fluids, ed. by R. Tao and G.D. Roy, World Scientific, Singapore, 643 (1994)
Chu SH, Lee SJ, Ahn KH, J. Rheol., 44(1), 105 (2000)
Cornell Theory Center, http://www.tc.cornell.edu/Smart-Nodes/Newsletters/MRI.series/ (1995)
Denn MM, Process Fluid Mechanics, Prentice-Hall, New Jersey (1980)
Havelka KO, Pialet JW, ChemTech, 36, 36 (1996)
Hwang K, Degroot D, Parallel Processing for Super Computers and Artificial Intelligence, MaGraw-Hill (1989)
Kim DH, Chu SH, Ahn KH, Lee SJ, Korean J. Rheol., 11(2), 82 (1999)
Klingenberg DJ, Zukoski CF, Langmuir, 6, 15 (1990)
Klingenberg DJ, J. Rheol., 37, 199 (1993)
Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 91, 7888 (1989)
Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 94, 6160 (1991)
Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 94, 6170 (1991)
Lukkarinen A, Kaski K, J. Appl. Phys., 83, 1717 (1998)
Russel WB, Saville DA, Schowalter WR, Colloidal Dispersions, Cambridge (1989)
Sproston JL, Stanway R, Faghmous A, Rev. Gen. Electr., Sep., 21 (1991)
Walker DW, http://www.epm.ornl.gov/~walker/mpi/ (1995)

[Referenced By]

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[1] Adriani PM, Gast AP, Phys. Fluids, 31, 2757 (1988)

[2] Ahn KH, Klingenberg DJ, J. Rheol., 38(3), 713 (1994)

[3] Brady JF, Bossis G, Ann. Rev. Fluid. Mech., 20, 111 (1988)

[4] Brooks DA, "Selection of Commercial ElectroRheological Device," in Proceedings of the Fourth International Conference on Electrorheological Fluids, ed. by R. Tao and G.D. Roy, World Scientific, Singapore, 643 (1994)

[5] Chu SH, Lee SJ, Ahn KH, J. Rheol., 44(1), 105 (2000)

[6] Cornell Theory Center, http://www.tc.cornell.edu/Smart-Nodes/Newsletters/MRI.series/ (1995)

[7] Denn MM, Process Fluid Mechanics, Prentice-Hall, New Jersey (1980)

[8] Havelka KO, Pialet JW, ChemTech, 36, 36 (1996)

[9] Hwang K, Degroot D, Parallel Processing for Super Computers and Artificial Intelligence, MaGraw-Hill (1989)

[10] Kim DH, Chu SH, Ahn KH, Lee SJ, Korean J. Rheol., 11(2), 82 (1999)

[11] Klingenberg DJ, Zukoski CF, Langmuir, 6, 15 (1990)

[12] Klingenberg DJ, J. Rheol., 37, 199 (1993)

[13] Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 91, 7888 (1989)

[14] Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 94, 6160 (1991)

[15] Klingenberg DJ, van Swol F, Zukoski CF, J. Chem. Phys., 94, 6170 (1991)

[16] Lukkarinen A, Kaski K, J. Appl. Phys., 83, 1717 (1998)

[17] Russel WB, Saville DA, Schowalter WR, Colloidal Dispersions, Cambridge (1989)

[18] Sproston JL, Stanway R, Faghmous A, Rev. Gen. Electr., Sep., 21 (1991)

[19] Walker DW, http://www.epm.ornl.gov/~walker/mpi/ (1995)